Nowadays, apparatuses in compliance with, for example, MPEG (Moving Picture Expert Group), which is an image compression standard based on orthogonal transformation, such as discrete cosine transformation, and motion compensation where redundancies specific to image information are exploited to handle images as digital signals for efficient transmission and accumulation of such digital signals, are being widely used for both information distribution by broadcast stations and information reception in households.
In particular, the MPEG2 (ISO/IEC 13818-2) compression technique is a standard defined as a general-purpose image compression scheme, covering interlaced scan images and progressive scan images, as well as standard-resolution images and high-definition images. Thus, MPEG2 is widely used by both professionals and general consumers, as seen in, for example, the DVD (Digital Versatile Disk) standards.
The use of the MPEG2 compression scheme accomplishes a high compression ratio and high image quality by assigning bit rates of, for example, 4 to 8 Mbps for interlaced scan images with a standard resolution of 720×480 pixels and bit rates of, for example, 18 to 22 Mbps for interlaced scan images with a high resolution of 1920×1088 pixels.
Since MPEG2 is mainly intended for a high quality encoding technique suitable for broadcasting, it does not support an encoding scheme for a higher compression ratio. This is the reason the MPEG4 encoding system has been standardized as an encoding scheme for a higher compression ratio. The image encoding scheme was approved as an international standard ISO/IEC 14496-2 in December 1998.
Furthermore, the standardization of H.26L (ITU-T Q6/16 VCEG), originally intended for image encoding for video conferences, is being promoted by ITU-T (International Telecommunication Union-Telecommunication Standardization Sector).
H.26L is known as a standard which achieves a higher encoding efficiency, though it requires a larger amount of arithmetic operation for encoding processing and decoding processing compared with known encoding schemes such as MPEG2 and MPEG4.
In addition, one of the current MPEG4 activities includes Joint Model of Enhanced-Compression Video Coding, being promoted jointly with ITU-T, for the standardization of an encoding scheme which achieves a higher encoding efficiency based on H.26L and employs functions not supported by H.26L.
A known image information encoding apparatus based on orthogonal transformation, such as discrete cosine transformation or Karhunen-Loeve transform, and motion compensation will now be described with reference to FIG. 1. FIG. 1 shows an example structure of a known image information encoding apparatus.
In the relevant image information encoding apparatus, an input image signal, as an analog signal, is converted to a digital signal by an A/D conversion section 1 and the digital signal is then passed to a picture sorting buffer 2. The picture sorting buffer 2 rearranges frames of the image information from the A/D conversion section 1 according to the GOP (Group of Pictures) structure of the image compression information output by the relevant image information encoding apparatus.
Images that are subjected to intra-encoding (encoding in an image) will first be described. In the picture sorting buffer 2, the image information of an image to be subjected to intra-encoding is passed to an orthogonal transformation section 4 via an adder 3.
In the orthogonal transformation section 4, the image information is subjected to orthogonal transformation (e.g., discrete cosine transformation or Karhunen-Loeve transform), and the obtained transform coefficient is passed to a quantization section 5. In the quantization section 5, the transform coefficient supplied from the orthogonal transformation section 4 is subjected to quantization processing under the control of a rate control section 8 based on the amount of transform coefficient data accumulated in an accumulation buffer 7.
In a lossless encoding section 6, an encoding mode is determined based on the quantized transform coefficient, quantization scale, etc. supplied from the quantization section 5, and the determined encoding mode is subjected to lossless encoding (e.g., variable-length encoding or arithmetic coding) to form information to be stored in the header of an image encoding unit. Furthermore, the encoded encoding mode is supplied to the accumulation buffer 7 for accumulation. The encoded encoding mode accumulated in the accumulation buffer 7 is output to the subsequent stage as image compression information.
In addition, in the lossless encoding section 6, the quantized transform coefficient is subjected to lossless encoding and the encoded transform coefficient is accumulated in the accumulation buffer 7. The encoded transform coefficient, accumulated in the accumulation buffer 7, is also output to the subsequent stage as image compression information.
In a dequantization section 9, the transform coefficient quantized by the quantization section 5 is dequantized. In an inverse orthogonal transformation section 10, the dequantized transform coefficient is subjected to inverse orthogonal transformation processing and decoded image information is generated. The generated decoded image information is accumulated in a frame memory 11.
Images that are subjected to inter-encoding (encoding between images) will now be described. In the picture sorting buffer 2, the image information of an image to be subjected to inter-encoding is supplied to the adder 3 and a motion prediction/compensation section 12.
In the motion prediction/compensation section 12, image information for reference that corresponds to the image from the picture sorting buffer 2 that is subjected to inter-encoding is read out from the frame memory 11 and then subjected to motion prediction/compensation processing to generate reference image information, which is then supplied to the adder 3. Furthermore, motion vector information obtained as a result of motion prediction/compensation processing in the motion prediction/compensation section 12 is supplied to the lossless encoding section 6.
In the adder 3, the reference image information from the motion prediction/compensation section 12 is converted to a differential signal from the image information of the image from the picture sorting buffer that is subjected to inter-encoding.
When an image which is subjected to inter-encoding is to be processed, the differential signal is subjected to orthogonal transformation in the orthogonal transformation section 4, and the obtained transform coefficient is supplied to the quantization section 5. In the quantization section 5, the transform coefficient supplied from the orthogonal transformation section 4 is subjected to quantization processing under the control of the rate control section 8.
In the lossless encoding section 6, an encoding mode is determined based on the transform coefficient and the quantization scale quantized by the quantization section 5, as well as the motion vector information supplied from the motion prediction/compensation section 12 and other information. The determined encoding mode is then subjected to lossless encoding to generate information to be stored in the header of an image encoding unit. The encoded encoding mode is accumulated in the accumulation buffer 7. The encoded encoding mode accumulated in the accumulation buffer 7 is output as image compression information.
Furthermore, in the lossless encoding section 6, motion vector information from the motion prediction/compensation section 12 is subjected to lossless encoding processing to generate information to be stored in the header of the image encoding unit.
When an image which is subjected to inter-encoding is to be processed, the processing in the dequantization section 9 and the subsequent processing are carried out in the same manner as with intra-encoding, and will not be described.
A known image information decoding apparatus which receives image compression information output by the known image information encoding apparatus shown in FIG. 1 to restore an image signal will now be described with reference to FIG. 2. FIG. 2 shows an example structure of a known image information decoding apparatus.
In the relevant image information decoding apparatus, image compression information which has been input is temporarily stored in an accumulation buffer 21 and transferred to a lossless decoding section 22. The lossless decoding section 22 applies lossless decoding (e.g., variable-length decoding or arithmetic decoding) to the image compression information based on a predetermined format of image compression information to acquire the encoding mode information stored in the header and supplies it to a dequantization section 23. The lossless decoding section 22 also acquires the quantized transform coefficient to supply it to the dequantization section 23. Furthermore, if the frame to be decoded has been subjected to inter-encoding, the lossless decoding section 22 also decodes the motion vector information stored in the header of the image compression information and supplies the information to a motion prediction/compensation section 28.
The dequantization section 23 dequantizes the quantized transform coefficient supplied from the lossless decoding section 22, and supplies the obtained transform coefficient to an inverse orthogonal transformation section 24. The inverse orthogonal transformation section 24 applies inverse orthogonal transformation (e.g., inverse discrete cosine transformation or inverse Karhunen-Loeve transform) to the transform coefficient based on a predetermined format of the image compression information.
If the relevant frame has been subjected to intra-encoding, the image information subjected to inverse orthogonal transformation is stored in a picture sorting buffer 26 via an adder 25, converted to an analog signal by a D/A conversion section 27, and then output to the subsequent stage. The image information subjected to inverse orthogonal transformation is also stored in a frame memory 29.
Furthermore, if the relevant frame has been subjected to inter-encoding, a reference image is generated in the motion prediction/compensation section 28 based on the motion vector information from the lossless decoding section 22 and the image information stored in the frame memory 29 and is then supplied to the adder 25. In the adder 25, the reference image from the motion prediction/compensation section 28 is combined with the output from the inverse orthogonal transformation section 25 to generate image information. The other processing is carried out in the same manner as with a frame subjected to intra-encoding and will not be described.
According to H.26L, two types of encoding: UVLC (Universal Variable Length Code), one type of variable-length encoding, and CABAC (Context-based adaptive binary arithmetic coding), one type of arithmetic coding, are defined as lossless encoding schemes. Thus, the user can select one of UVLC and CABAC as a lossless encoding scheme. The information indicating whether the lossless encoding scheme used is UVLC or CABAC is specified in the field called Entropy Coding included in the RTP Parameter Set Packet of the RTP layer in the image compression information.
Arithmetic coding, to which CABAC belongs, will now be described. In arithmetic coding, any message (including a plurality of alphabetic symbols) is represented as one point in a semi-open interval 0.0≦x<1.0, and the code is generated based on the coordinates of this point.
First, the semi-open interval 0.0≦x<1.0 is divided into subintervals, each corresponding to a symbol, on the basis of the occurrence probabilities of the symbols included in the alphabetic sequence.
FIG. 3 shows an example of the occurrence probabilities of symbols s1 to s7 with their respective subintervals. In arithmetic coding, the upper limit and the lower limit of a subinterval are determined on the basis of the cumulative occurrence probability of each symbol, as shown in FIG. 3. The lower limit of the subinterval for the symbol si (i=1, 2, . . . , 7) is equal to the upper limit of the subinterval for the preceding symbol si-1, and the upper limit of the subinterval for the symbol si is equal to the value obtained by adding the occurrence probability of the symbol si to the lower limit of the subinterval for the symbol si.
Let us assume that (s2s1s3s6s7) is input as a message. Here, the symbol s7 is assumed to be a terminal symbol which represents the end of the message. In short, the message ends with this terminal symbol. The arithmetic coding scheme calculates a subinterval corresponding to each symbol included in the message (s2s1s3s6s7), as shown in FIG. 4. In other words, the interval assigned as shown in FIG. 3 is divided in proportion to the cumulative occurrence probability of the subsequent symbol. The subinterval obtained finally is the range which includes the value representing the message. In this manner, any value in this range can uniquely restore the corresponding message. It is noted, however, that a value that can be represented by a power of two in the semi-open interval is used to represent the message, taking the encoding efficiency into consideration.
More specifically, in this example, the value obtained by Expression (2) shown below represents the message included in the semi-open interval 0.21164≦x<0.2117 on the basis of Expressions (1) shown below.
                                          2                          -              1                                =          0.5                ⁢                                  ⁢                              2                          -              2                                =          0.25                ⁢                                  ⁢                              2                          -              3                                =          0.125                ⁢                                  ⁢                              2                          -              4                                =          0.0625                ⁢                                  ⁢                              2                          -              5                                =          0.03125                ⁢                                  ⁢                              2                          -              6                                =          0.015625                ⁢                                  ⁢                              2                          -              7                                =          0.0078125                ⁢                                  ⁢                              2                          -              8                                =          0.00390625                ⁢                                  ⁢                              2                          -              9                                =          0.001953125                ⁢                                  ⁢                              2                          -              10                                =          0.0009765625                ⁢                                  ⁢                              2                          -              11                                =          0.00048828125                ⁢                                  ⁢                              2                          -              12                                =          0.000244140625                ⁢                                  ⁢        ⋮                            (        1        )                                                      2                          -              3                                +                      2                          -              4                                +                      2                          -              6                                +                      2                          -              7                                +                      2                          -              11                                +                      2                          -              12                                      =        0.211669921875                            (        2        )            
Thus, a code length of 12 bits is sufficient for the length of the code corresponding to the message (s2s1s3s6s7) so that a value from 2−1 to 2−12 can be represented to encode the message (s2s1s3s6s7) into (001101100011).
CABAC defined in H.26L will now be described. Details of CABAC are described in a document “Video Compression Using Context-Based Adaptive Arithmetic Coding”, Marpe et al, ICIO1 (hereinafter, referred to as Document 1). CABAC has the following three features, compared with UVLC, which is also defined in H.26L.
A first feature is a capability of eliminating the redundancy between symbols by using a context model appropriate for each symbol to be encoded to carry out arithmetic coding based on an independent probability model.
A second feature is a capability of assigning a bit rate of a non-integer value to each symbol in arithmetic coding, i.e., a capability of achieving an encoding efficiency similar to that of entropy.
For example, statistical data of a motion vector is variable in space and time, as well as with respect to bit rates and sequences. A third feature enables encoding in response to such variations to be carried out by applying adaptive encoding.
FIG. 5 shows a typical structure of a CABAC encoder to which CABAC is applied. In the relevant CABAC encoder, a context modeling section 31 first converts the symbol of any syntax element in image compression information to an appropriate context model according to the history. Such modeling is called context modeling. The context model for each syntax element in image compression information will be described below.
A binarization section 32 binarizes a symbol which is not binarized. In an adaptive binary arithmetic coding section 33, the binarized symbol is then subjected to probability estimation by a probability estimation section 34, and is subjected to adaptive arithmetic coding by an encoding engine 35 based on the probability estimation. After adaptive arithmetic coding processing has been carried out, the related models are updated, and each model can carry out encoding processing according to the statistics of actual image compression information.
Here, context models for carrying out arithmetic coding of MB_type (MB_type), motion vector information (MVD), and reference frame parameter (Ref_frame), which are syntax elements in image compression information, will now be described.
Context model generation for MB_type will be described for each of two cases: a case of intra-frame and a case of inter-frame.
If macroblocks A, B, and C are arranged as shown in FIG. 6 on an intra-frame, the context model ctx_mb_type_intra(C) corresponding to the MB_type of the macroblock C is defined according to Expression (3) shown below. The mode of a macroblock on an intra-frame is Intra4×4 or Intra16×1.ctx_mb_type_intra(C)=A+B  (3)
In Expression (3), A is 0 when the macroblock A is Intra4×4 or 1 when the macroblock A is Intra16×16. Similarly, B is 0 when the macroblock B is Intra4×4 or 1 when the macroblock B is Intra16×16. Therefore, the context model ctx_mb_type_intra(C) takes one of 0, 1, and 2.
If the macroblocks A, B, and C are arranged as shown in FIG. 6 on an inter-frame which is a P picture, the context model ctx_mb_type_inter(C) corresponding to the MB_type of the macroblock C is defined according to Expression (4) shown below. If the relevant inter-frame is a B picture, the context model ctx_mb_type_inter(C) is defined according to Expression (5) shown below.ctx_mb_type_inter(C)=((A==Skip)?0:1)+((B==Skip)?0:1)  (4)ctx_mb_type_inter(C)=((A==Direct)?0:1)+((B==Direct)?0:1)  (5)
In Expression (4), the operator ((A==Skip)?0:1) indicates 0 if the macroblock A is in the Skip mode or 1 if the macroblock A is not in the Skip mode. Similarly, the operator ((B==Skip)?0:1) indicates 0 if the macroblock B is in the Skip mode or 1 if the macroblock B is not in the Skip mode.
In Expression (5), the operator ((A==Direct)?0:1) indicates 0 if the macroblock A is in the Direct mode or 1 if the macroblock A is not in the Direct mode. Similarly, the operator ((B==Direct)?0:1) indicates 0 if the macroblock B is in the Direct mode or 1 if the macroblock B is not in the Direct mode.
Therefore, there are three types of the context model ctx_mb_type_inter(C) corresponding to the MB_type of the macroblock C on an inter-frame (P picture) for each of the P picture and the B picture.
Context model generation for motion vector information (MVD) will now be described.
Motion vector information corresponding to the macroblock of interest included in image compression information is encoded as prediction errors from the motion vector corresponding to the neighboring macroblocks. The evaluation function ek(C) for the macroblock C of interest, from among the macroblocks A, B, and C arranged as shown in FIG. 7, is defined according to Expression (6) shown below. In Expression (6), k=0 indicates the horizontal component, whereas k=1 indicates the vertical component.ek(C)=|mvdk(A)|+|mvdk(B)|  (6)
Here, mvdk(A) and mvdk(B) indicate motion vector prediction errors with respect to the macroblocks A and B, respectively, neighboring the macroblock C.
In Expression (6), if the macroblock C is disposed at the left edge of the picture frame, i.e., if one of the macroblocks A and B does not exist, information related to the corresponding motion vector prediction error mvdk(A) or mvdk(B) cannot be obtained, and hence the corresponding item in the right-hand member of Expression (6) is ignored. The context model ctx_mvd(C,k) corresponding to ek(C) defined as described above is defined according to Expressions (7-1) to (7-3) below.ctx_mvd(C,k)=0 ek(C)<3  (7-1)ctx_mvd(C,k)=1 32<ek(C)  (7-2)ctx_mvd(C,k)=2 3≦ek(C)≦32  (7-3)
Context model generation for the motion vector information (MVD) is carried out as shown in FIG. 8. More specifically, the motion vector prediction error mvdk(C) for the macroblock C is divided into the absolute value |mvdk(C)| and the sign. The absolute value |mvdk(C)| is binarized. The first bin (the leftmost value) of the binarized absolute value |mvdk(C)| is encoded using the above-described context model ctx_mvd(C,k). The second bin (the second value from the left) is encoded using context model 3. Similarly, the third and fourth bins are encoded using context models 4 and 5, respectively. The fifth bin and the subsequent bins are encoded using context model 6. The sign of mvdk(C) is encoded using context model 7. As described above, motion vector information (MVD) is encoded using eight types of context models.
Context models for encoding the reference frame parameter (Ref_frame) will now be described.
When two or more reference frames are used for an inter-frame, information related to the reference frame is set for each macroblock of the inter-frame. If the reference frame parameters for the macroblocks A and B are represented as A and B, respectively, with respect to the macroblocks A, B, and C arranged as shown in FIG. 6, the context model ctx_ref_frame(C) for the macroblock C is defined according to Expression (8) shown below.ctx_ref_frame(C)=((A==0)?0:1)+2((B==0)?0:1)  (8)
In Expression (8), the operator ((A==0)?0:1) is 0 when the reference frame parameter for the macroblock A is 0 or 1 when the reference frame parameter for the macroblock A is not 0. Similarly, the operator ((B==0)?0:1) is 0 when the reference frame parameter for the macroblock B is 0 or 1 when the reference frame parameter for the macroblock B is not 0.
Thus, four types of context models for encoding the reference frame parameter (Ref_frame) are defined according to Expression (8). Furthermore, the context model for the second bin and the context models for the third bin and the subsequent bins are defined.
Context models for arithmetically encoding the code block pattern (CBP), which is a syntax element related to the texture information included in the image compression information according to H.26L, the intra-prediction mode (IPRED), and the (RUN,LEVEL) information will now be described.
The description starts with context models related to the code block pattern. The handling of code block patterns other than an Intra16×16 macroblock is defined as follows.
That is, as the CBP bits for the luminance signal, one CBP bit is included in each of four 8×8 blocks of an Intra16×16 macroblock, i.e., a total of four CBP bits. When the macroblocks A, B, and C are arranged as shown in FIG. 6, the context model ctx_cbp_luma(C) corresponding to the luminance signal of the macroblock C is defined according to Expression (9) shown below.ctx_cbp_luma(C)=A+2B  (9)
In Expression (9), A indicates the CBP bit of the luminance signal of the macroblock A, and B indicates the CBP bit of the luminance signal of the macroblock B.
The remaining two bits in the CBP field are related to the chrominance signal. The context model ctx_cbp_chroma_sig(C) corresponding to the chrominance signal of the macroblock C is defined according to Expression (10) shown below.ctx_cbp_chroma_sig(C)=A+2B  (10)
In Expression (10), A indicates the CBP bit of the chrominance signal of the macroblock A, and B indicates the CBP bit of the chrominance signal of the macroblock B. Here, if the context model ctx_cbp_chroma_sig(C) corresponding to the chrominance signal of the macroblock C is not 0, i.e., if the AC components of the chrominance signal exist, the context model ctx_cbp_chroma_ac(C) corresponding to the AC components of the chrominance signal of the macroblock C defined according to Expression (11) shown below needs to be encoded.ctx_cbp_chroma_ac(C)=A+2B  (11)
In Expression (11), A indicates the cbp_chroma_ac decision corresponding to the macroblock A, and B indicates the cbp_chroma_ac decision corresponding to the macroblock B.
Since the context models defined according to Expressions (9) to (11) are defined separately for the intra-macroblock and the inter-macroblock, a total of 24 (=2×3×4) types of context models are defined.
Furthermore, in the case of an Intra16×16 macroblock, one type of context model is defined for the binarized AC decision, and one type of context model is defined for each component of the chrominance signal.
Context models related to the intra-prediction mode (IPRED) will now be described. Six types of intra-prediction modes (label 0 to 5) defined in H.26L will now be described with reference to FIGS. 9 and 10. FIG. 9 shows pixels a to p existing in a 4×4 block generated by dividing a macroblock and pixels A to I existing in the neighboring 4×4 blocks. Labels 1 to 5 in FIG. 10 indicate intra-prediction modes with different directions. The intra-prediction mode indicated by label 0 is a DC prediction mode (DC Prediction).
In the intra-prediction mode of label 0, the pixels a to p are predicted according to Expression (12) shown below.pixels a to p=(A+B+C+D+E+F+G+H)//8  (12)In Expressions (12) to (15), A to I indicate the pixels A to I, respectively, and the symbol “//” means an arithmetic operation such that the result of division is rounded off.
In the intra-prediction mode indicated by label 0, if four pixels (e.g., the pixels A to D) of the eight pixels A to H do not exist in the picture frame, Expression (12) is not used and the mean value of the remaining four pixels (the pixels E to H n this case) is used as predicted values for the pixels a to p. Furthermore, if none of the eight pixels A to H exists in the picture frame, Expression (12) is not used and a predetermined value (e.g., 128) is used as predicted values of the pixels a to p.
The intra-prediction mode indicated by label 1 is called Vertical/Diagonal Prediction. The intra-prediction mode of label 1 is used only when the four pixels A to D exist in the picture frame. In this case, the pixels a to p are predicted according to Expressions (13-1) to (13-6) shown below.pixel a=(A+B)//2  (13-1)pixel e=B  (13-2)pixels b,i=(B+C)//2  (13-3)pixels f,m=C  (13-4)pixels c,j=(C+D)//2  (13-5)pixels d,g,h,k,l,n,o,p=D  (13-6)
The intra-prediction mode indicated by label 2 is called Vertical Prediction. The intra-prediction mode of label 2 is used only when the four pixels A to D exist in the picture frame. In this case, the pixel A is used as predicted values of, for example, the pixels a, e, i, and m, and the pixel B is used as predicted values of, for example, the pixels b, f, j, and n.
The intra-prediction mode indicated by label 3 is called Diagonal Prediction. The intra-prediction mode of label 1 is used only when the nine pixels A to I exist in the picture frame. In this case, the pixels a to p are predicted according to Expressions (14-1) to (13-7) shown below.pixel m=(H+2G+F)//4  (14-1)pixels i,n=(G+2F+E)//4  (14-2)pixels e,j,o=(F+2E+I)//4  (14-3)pixels a,f,k,p=(E+2I+A)//4  (14-4)pixels b,g,l=(I+2A+B)//4  (14-5)pixels c,h=(A+2B+C)//4  (14-6)pixel d=(B+2C+D)//4  (14-7)
The intra-prediction mode indicated by label 4 is called Horizontal Prediction. The intra-prediction mode of label 4 is used only when the four pixels E to H exist in the picture frame. In this case, the pixel E is used as predicted values of, for example, the pixels a, b, c, and d, and the pixel F is used as predicted values of, for example, the pixels e, f, g, and h.
The intra-prediction mode indicated by label 5 is called Horizontal/Diagonal Prediction. The intra-prediction mode of label 5 is used only when the four pixels E to H exist in the picture frame. In this case, the pixels a to p are predicted according to Expressions (15-1) to (15-6) shown below.pixel a=(E+F)//2  (15-1)pixel b=F  (15-2)pixels c,e=(F+G)//2  (15-3)pixels f,d=G  (15-4)pixels i,g=(G+H)//2  (15-5)pixels h,j,k,l,m,n,o,p=H  (15-6)
Two context models are defined for each of the intra-prediction modes of labels 0 to 5. More specifically, one of the two context models is the first bin for each mode and the other of the two context models is the second bin for each mode. In addition to these context models, one context model is defined for each of the two bits in the Intra16×16 mode. Therefore, a total of 14 context models are defined for the intra-prediction mode.
Context models related to (RUN,LEVEL) will now be described.
In H.26L, two types of scan methods shown in FIGS. 11A and 11B are defined as methods for rearranging a two-dimensional discrete cosine transform coefficient into a one-dimensional coefficient. The single scan technique shown in FIG. 11A is used for the luminance signal of an intra-macroblock in a case other than that where the quantization parameter QP is smaller than 24. The double scan technique shown in FIG. 11B is used when the single scan technique is not used.
In an inter-macroblock and an intra-macroblock with a quantization parameter QP of 24 or larger, an average of one non-zero coefficient exists for a 4×4 macroblock, in short, a one-bit EOB (End Of Block) signal is sufficient. For the luminance signal of an intra-macroblock with a quantization parameter QP smaller than 24, two or more non-zero coefficients exist, and a one-bit EOB signal is not sufficient. This is the reason that the double scan technique shown in FIG. 11B is used.
As shown in FIG. 12, nine types of context models are defined for (RUN,LEVEL) according to the discrimination of the above-described scan method, the discrimination between DC block type and AC block type, the discrimination between luminance signal and chrominance signal, and the discrimination between intra-macroblock and inter-macroblock.
The LEVEL information is separated into the sign and the absolute value. Four context models are defined according to the corresponding Ctx_run_level shown in FIG. 12. More specifically, the first context model is defined for the sign, the second context model is defined for the first bin, the second context model is defined for the second bin, and the fourth context model is defined for the subsequent bins.
When LEVEL is not 0 (i.e., the LEVEL is not an EOB), RUN described below is encoded. For RUN, two context models are defined for each Ctx_run_level shown in FIG. 12: one for the first bin and the other for the second and subsequent bins.
Context models for the quantization-related parameter Dquant that can be set at the macroblock level in image compression information according to H.26L will now be described.
The parameter Dquant is set when the code block pattern for the macroblock includes a non-zero orthogonal transform coefficient or the macroblock is 16×16 Intra Coded. The parameter Dquant can range from −16 to 16. The quantization parameter QUANTnew for the macroblock is calculated according to Expression (16) shown below that uses the parameter Dquant in the image compression information.QUANTnew=modulo32(QUANTold+Dquant+32)  (16)In Expression (16), QUANTold is the quantization parameter used for the previous encoding or decoding.
The first context model ctx_dquant(C) for the parameter Dquant of the macroblock C arranged as shown in FIG. 6 is defined according to Expression (17) shown below.ctx_dquant(C)=(A!=0)  (17)In Expression (17), A indicates the value of the parameter Dquant of the macroblock A. The second context model is defined for the first bin and the second context model is defined for the second and the subsequent bins.
If a symbol which is input to the context models described above is not binarized, the symbol must be binarized before it can be input to the context models. Syntax elements other than MB_type are binarized according to the relationships shown in FIG. 13.
MB_type, ten types of which are defined for the P picture, is binarized according to the relationship shown in FIG. 14A. Furthermore, MB_type, 17 types of which are defined for the B picture, is binarized according to the relationships shown in FIG. 14B.
Registers for the above-described various context models are pre-initialized with pre-calculated values, and when a symbol is to be encoded, the occurrence frequencies of the bins for a series of context models are successively updated for a determination in the encoding of the subsequent symbol.
If the occurrence frequency for a given context model exceeds a predetermined value, the frequency counter is scaled down. Through such periodic scaling processing, dynamic occurrence of symbols can be handled easily.
For the arithmetic coding scheme for binarized symbols in H.26L, the approach disclosed in a document “Arithmetic Coding for Data Compression”, (Witten et al. Comm. of the ACM, 30 (6), 1987, pp 520-541) (hereinafter, referred to as Document 2) is applied, as of this writing.
In MPEG2, if an image signal to be input is of interlaced scan format, field/frame adaptive encoding processing can be carried out at the macroblock level.
Although such specifications are not defined in H.26L at present, a document “Interlace Coding Tools for H.26L Video Coding (L. Wang et al., VCEG-037, December 2001)” (hereinafter, referred to as Document 3) proposes that the H.26L specifications be extended to support field/frame adaptive encoding processing at the macroblock level.
The field/frame adaptive encoding processing at the macroblock level proposed in Document 3 will now be described.
According to the current H.26L, seven types of modes (modes 1 to 7), as shown in FIG. 15, are defined as units of motion prediction/compensation in a macroblock.
Document 3 proposes that a frame/field flag be disposed between Run and MB_type as the syntax corresponding to the macroblock in image compression information, as shown in FIG. 16. If the value of the frame/field flag is 0, it indicates that the relevant macroblock is to be subjected to frame-based encoding. In contrast, if the value of the frame/field flag is 1, it indicates that the relevant macroblock is to be subjected to field-based encoding.
If the value of the frame/field flag is 1, i.e., if field-based encoding is to be applied, the pixels in the macroblock are rearranged row by row, as shown in FIG. 17.
If the value of the frame/field flag is 1, five types of modes (modes 1a to 5a), as shown in FIG. 18, i.e., the five types of modes corresponding to the modes 3 to 7 in FIG. 15, are defined as units of motion prediction/compensation in the macroblock.
For example, in the mode 2a of FIG. 18, the blocks 0 and 1 out of the four 8×8 blocks 0 to 3 generated by dividing the macroblock belong to the same field parity, and the blocks 2 and 3 belong to the same field parity. Furthermore, for example, in the mode 3a of FIG. 18, the blocks 0 to 3 of the eight 4×8 blocks 0 to 8 generated by dividing the macroblock belong to the same field parity, and the blocks 4 to 7 belong to the same field parity.
The intra-prediction mode when the value of the frame/field flag is 1 will now be described. For example, the pixels a to p disposed in the 4×4 block shown in FIG. 9 are subjected to intra-prediction using the pixels A to I disposed in the neighboring 4×4 blocks, also when the value of the frame/field flag is 1. In this case, it should be noted that all of the pixels a to p and the pixels A to I belong to the same field parity.
A description when the pixels A to I and the pixels a to p belong to the same macroblock will now be given with reference to FIG. 19. The pixels a to p existing in the 4×4 block 7 generated by dividing the macroblock into 16 are subjected to intra-prediction using the pixels A to I disposed at the edges of the neighboring blocks 2, 3, and 6.
A description when the pixels A to I belong to a macroblock different from that of the pixels a to p will now be given with reference to FIGS. 20A and 20B.
FIG. 20A shows that the frame/field flag values of the macroblocks to the left of and above the macroblock for processing are 1. In this case, the intra-prediction of the pixels existing in the 4×4 block C generated by dividing the target macroblock into 16 is carried out based on the pixels in the 4×4 block A generated by dividing the macroblock to the left into 16 and the pixels in the 4×4 block B generated by dividing the macroblock above into 16. The intra-prediction of the pixels existing in the 4×4 block C′ is carried out based on the pixels existing in the 4×4 block A′ and the pixels existing in the 4×4 block B′.
FIG. 20B shows an example where the value of the frame/field flag for the target macroblock for processing is 1 and the values of the frame/field flags for the macroblocks to the left and above are 0. In this case, the intra-prediction of the pixels existing in the 4×4 block C generated by dividing the target macroblock into 16 is carried out based on the pixels in the 4×4 block A generated by dividing the macroblock to the left into 16 and the pixels in the 4×4 block B generated by dividing the macroblock above into 16. The intra-prediction of the pixels existing in the 4×4 block C′ is carried out based on the pixels existing in the 4×4 block A′ and the pixels existing in the 4×4 block B′.
Intra-prediction of the chrominance signal will now be described with reference to FIG. 21. When the value of the frame/field flag is 1, only one type of intra-prediction mode for the chrominance signal is defined.
A to D in FIG. 21 each represent a 4×4 block of the chrominance signal. The blocks A and B belong to the first field and the blocks C and D belong to the second field. s0 to s2 are the sum of the chrominance signals existing in the blocks which belong to the first field parity and neighbor the blocks A to D. s3 to s5 are the sum of the chrominance signals existing in the blocks which belong to the second field parity and neighbor the blocks A to D.
The predicted values A to D respectively corresponding to the blocks A to D are predicted according to Expressions (18) shown below provided that s0 to s5 all exist in the picture frame.A=(s0+s2+4)/8B=(s1+2)/4C=(s3+s5+4)/8D=(s4+2)/4  (18)
If only s0, s1, s3, and s4 of s0 to s5 exist in the picture frame, the predicted values A to D respectively corresponding to the blocks A to D are predicted according to Expressions (19) shown below.A=(s0+2)/4B=(s1+2)/4C=(s3+2)/4D=(s4+2)/4  (19)
Furthermore, if only s2 and s5 of s0 to s5 exist in the picture frame, the predicted values corresponding to the blocks A to D are predicted according to Expressions (20) shown below.A=(s2+2)/4B=(s2+2)/4C=(s5+2)/4D=(s5+2)/4  (20)
FIG. 22 shows a method for encoding the residual components of the chrominance signal after intra-prediction has been applied as described above. More specifically, each of the 4×4 blocks is subjected to orthogonal transformation processing, the 2×2 blocks as shown in the figure are generated using the DC components of the first field and the second field, and orthogonal transformation processing is again applied.
Motion prediction/compensation processing when the value of the frame/field flag is 1 will now be described. When the value of the frame/field flag is 1, there are six types of motion prediction/compensation modes: an inter-16×16 mode, an inter-8×16 mode, an inter-8×8 mode, an inter-4×8 mode, and an inter-4×4 mode.
For example, the inter-16×16 mode is a mode in which the motion vector information for the first field, the motion vector information for the second field, and the reference frame in the inter-8×16 mode are equivalent.
These six types of motion prediction/compensation modes are respectively assigned Code_Numbers 0 to 5.
In the current H.26L, a multiple-frame prediction for allowing a plurality of reference frames as shown in FIG. 23 to be provided is specified. In the current frame-based H.26L standard, information related to reference frames is defined at the macroblock level such that the previously encoded frame is assigned Code_Number 0, and the frames one to five times preceding the frame with Code_Number 0 are respectively assigned Code_Number 1 to Code_Number 5.
On the other hand, for field-based encoding, the first field of the previously encoded frame is assigned Code_Number 0, and the second field of the same frame is assigned Code_Number 1. The first field of the frame preceding the frame with Code_Number 0 is assigned Code_Number 2 and the second field of the relevant frame is assigned Code_Number 3. The first field of the frame preceding the frame with Code_Number 2 is assigned Code_Number 4 and the second field of the relevant frame is assigned Code_Number 5.
Furthermore, for macroblocks that are subjected to field-based encoding, the reference field for the first field and the reference field for the second field are specified separately from each other.
The median prediction specified in the current H.26L will now be described with reference to FIG. 24, followed by the description of a motion vector information prediction method when the value of the frame/field flag is 1. The 16×16, 8×8, or 4×4 motion vector information corresponding to the 16×16 macroblock E shown in FIG. 24 is predicted using the median of the motion vector information of the neighboring macroblocks A to C.
Any of the macroblocks A to C that does not exist in the picture frame, however, is assumed to have a motion vector information value of 0 for median calculation. If, for example, the macroblocks D, B, and C do not exist in the picture frame, the motion vector information corresponding to the macroblock A is used as the predicted value. Furthermore, if the macroblock C does not exist in the picture frame, the median is calculated using the motion vector information of the macroblock D instead of the macroblock C.
The reference frames for the macroblocks A to D do not need to be the same.
A description when the block size of the macroblock is 8×16, 16×8, 8×4, or 4×8 will now be given with reference to FIGS. 25A to 25D. The macroblock E of interest and the neighboring macroblocks A to D are assumed to be arranged as shown in FIG. 24.
FIG. 25A shows an example where the block sizes of the macroblocks E1 and E2 are 8×16. For the left-hand macroblock E1, if the neighboring macroblock A to the left refers to the same frame as the macroblock E1, the motion vector information of the macroblock A is used as the predicted value. If the neighboring macroblock A to the left refers to a frame different from that referred to by the macroblock E1, the above-described median prediction is applied.
For the right-hand macroblock E2, if the neighboring macroblock C to the upper right refers to the same frame as the macroblock E2, the motion vector information of the macroblock C is used as the predicted value. If the neighboring macroblock C to the upper right refers to a frame different from that referred to by the macroblock E2, the above-described median prediction is applied.
FIG. 25B shows an example where the block sizes of the macroblocks E1 and E2 are 16×8. For the upper macroblock E1, if the neighboring macroblock B above refers to the same frame as the macroblock E1, the motion vector information of the macroblock B is used as the predicted value. If the neighboring macroblock B above refers to a frame different from that referred to by the macroblock E1, the above-described median prediction is applied.
For the lower macroblock E2, if the neighboring macroblock A to the left refers to the same frame as the macroblock E2, the motion vector information of the macroblock A is used as the predicted value. If the neighboring macroblock A to the left refers to a frame different from that referred to by the macroblock E2, the above-described median prediction is applied.
FIG. 25C shows an example where the block sizes of the macroblocks E1 to E8 are 8×4. The above-described median prediction is applied for the left-hand macroblocks E1 to E4, and the motion vector information of the left-hand macroblocks E1 to E4 is used as the predicted values for the right-hand macroblocks E5 to E8.
FIG. 25D shows an example where the block sizes of the macroblocks E1 to E8 are 4×8. The above-described median prediction is applied for the upper macroblocks E1 to E4, and the motion vector information of the upper macroblocks E1 to E4 is used as the predicted values for the lower macroblocks E5 to E8.
Also, if the value of the frame/field flag is 1, the horizontal direction component of the motion vector information is predicted in compliance with the above-described method. For the vertical direction component, however, a field-based block and a frame-based block are mixed, and the following processing is carried out. The macroblock E of interest and the neighboring macroblocks A to D are assumed to be arranged as shown in FIG. 24.
When the macroblock E is to be subjected to frame-based encoding provided that one of the neighboring macroblocks A to D has been subjected to field-based encoding, the mean value between the vertical direction component of the motion vector information for the first field and the vertical direction component of the motion vector information for the second field is multiplied by two, and the result is used as an equivalent to the frame-based motion vector information for prediction processing.
When the macroblock E is to be subjected to field-based encoding provided that one of the neighboring macroblocks A to D has been subjected to frame-based encoding, the vertical direction component value of the motion vector information is divided by two, and the result is used as an equivalent to the field-based motion vector information for prediction processing.
According to Document 3, a syntax element necessary for field/frame encoding at the macroblock level is added, and furthermore, the semantics of a syntax element such as motion vector information is changed. Nevertheless, in Document 3, no new context model is introduced or an existing context model is not updated in response to the above-described addition and change. Thus, the information provided in Document 3 is not sufficient to carry out field/frame encoding at the macroblock level using the CABAC scheme.
CABAC is known as a scheme which achieves a higher encoding efficiency, though it requires a larger amount of arithmetic operation for encoding processing compared with UVLC, and therefore it is preferable that CABAC is available for field/frame encoding at the macroblock level even when input image information has an interlaced scan format.